Transforming Data Center Planning with IoT: A Case Study of an American Multinational Technology Company
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Life Sciences
- Transportation
Applicable Functions
- Logistics & Transportation
- Procurement
Use Cases
- Inventory Management
- Last Mile Delivery
Services
- Cloud Planning, Design & Implementation Services
- System Integration
About The Customer
The customer is an American multinational technology company that specializes in a wide range of Internet-related services and products. These include online advertising technologies, a search engine, cloud computing, software, and hardware. The company operates numerous data centers globally to support its diverse range of services. The company's business model requires a robust and efficient planning system for its servers and networking equipment. The company's exponential growth necessitates a scalable and predictable planning process that can support high growth and improve service levels.
The Challenge
The American multinational technology company, specializing in Internet-related services and products, was facing significant challenges in managing its global data centers. The company lacked an end-to-end material requirements planning system for capacity build-out, leading to issues with on-time delivery and inventory misalignment. The company's planning process for servers and networking equipment was highly complex and unworkable, causing disruptions in their data center delivery. Additionally, the company was unable to plan for the correct technology/supplier allocation mix, leading to artificial shortages. The company's manual processes were not scalable and were impacting predictability, cost coverages, and the ability to support the exponential growth of their business.
The Solution
The company partnered with o9 to establish a seamless integration and workflow between different processes such as forecast consumption, material planning, and capacity planning. This ensured a user-friendly planning experience and supported the high growth of their business. The company was able to create a detailed supply chain network representation for planning with o9. They also gained better visibility on constraints at the contract manufacturer, enabling them to perform exception-based planning and model supplier quota arrangements. The company implemented the Enterprise Knowledge Graph combined with o9’s advanced solver to optimize integrated constraint-based planning solutions. This improved cross-functional collaboration within the enterprise for over 800 users and provided reliable, time phased order signals to upstream suppliers to proactively mitigate risk, support high growth, and improve service levels.
Operational Impact
Quantitative Benefit
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